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Computer-Assisted Language Learning Using Spaced Repetition

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Computer-Assisted Language Learning Using Spaced Repetition MASARYKOVA UNIVERZITA F}w¡¢£¤¥¦§¨ AKULTA INFORMATIKY !"#$%&'()+,-./012345<yA| Computer-assisted language learning using spaced repetition DIPLOMA THESIS Bc. Daniel Keder Brno, 2009 Declaration I declare that this diploma thesis is my original work and I have worked it out on my own. Any sources of information and literature used in creating this document are properly cited in the bibliography part of this document. Advisor: doc. Ing. Michal Brandejs, CSc. ii Acknowledgement I would like to thank my advisor, doc. Ing. Michal Brandejs, CSc. and the whole IS MU development team, especially Mgr. Jan Kasprzak and RNDr. Miroslava Misakov´ a.´ Without their support and advice this work would never have come into being. iii Keywords spaced repetition, spacing effect, language learning, Dril, Information System MU iv Abstract This thesis attends to the technique of learning called spaced repetition. Spaced repetition helps the student to memorize a great number of small and relatively independent pieces of knowledge, such as a foreign language vocabulary. It is utilizing the psychological spacing effect. v Contents 1 Introduction .........................................3 2 What is spaced repetition .................................4 2.1 Spacing effect .....................................4 2.2 Learning process ...................................5 2.3 Forgetting curve ....................................6 2.4 Specifics of learning foreign languages .......................7 3 Spaced repetition software ................................8 3.1 SuperMemo ......................................8 3.2 Anki ..........................................9 3.3 Mnemosyne ...................................... 10 3.4 FullRecall ........................................ 11 4 Dril features ......................................... 12 4.1 Dril and other e-learning applications in IS MU .................. 12 4.2 Features ........................................ 12 4.3 Algorithm ....................................... 13 4.4 Overview of used technologies ........................... 15 4.5 Future .......................................... 17 5 Dril guide .......................................... 18 5.1 Subscribe to a coursebook .............................. 18 5.2 Learning ........................................ 18 5.3 Editing cards ...................................... 20 5.4 Notifying the user he has to learn .......................... 20 5.5 Erasing user data ................................... 21 5.6 Dril Management ................................... 22 5.7 Creating and editing coursebooks .......................... 22 5.8 Importing new cards ................................. 22 5.9 Format of the data file ................................ 24 5.10 Format of the template file .............................. 25 5.11 Viewing existing lessons and cards ......................... 27 5.12 How to use Dril effectively .............................. 27 6 Dril statistics ........................................ 28 6.1 Number of users .................................... 28 6.2 Average intervals ................................... 29 6.3 Interval, factor and level distributions ....................... 30 1 6.4 Forgetting curve .................................... 30 6.5 Amount of learning material ............................. 31 7 Conclusion .......................................... 35 A Code samples ........................................ 36 2 Chapter 1 Introduction This diploma thesis attends to the technique of learning called spaced repetition. Spaced repetition helps the student to memorize a great number of small and relatively indepen- dent pieces of knowledge, such as the foreign language vocabulary with as small effort as possible. Spaced repetition is using the psychological spacing effect. The spacing effect is known since the 19th century, but it could be conveniently utilized only with the advent of informa- tion technology. The reason is that the “administrative” tasks of the learning process could be done by a computer, thus liberating the student of this burden. It also enabled using of more complex algorithms, because they are no longer computed manually. The work consists of five chapters. The first chapter gives a short overview of what the spaced repetition is and how does it work. The second chapter contains a description of existing spaced repetition software. The third and fourth chapter are both devoted to Dril — a new application in the MU Information System that helps its users in learning. The third chapter contains overview of Dril features and used technology, whereas the fourth chapter provides exhaustive description of Dril. In the last chapter there are statistics of the application usage and summarized achievements of its users. 3 Chapter 2 What is spaced repetition Spaced repetition is a learning technique based on reviewing of the knowledge in increasing time intervals. It is designed to help the student memorize large amount of small indepen- dent pieces of knowledge with the following goals in mind: • Maximize amount of remembered information. • Minimize learning time. One can argue that there is no need to memorize anything — after all we have Internet and everybody can look up needed information in a few seconds. That is true. But human brain is very good at making associations and if we want it to work effectively, we have to “load the data into memory” first. Spaced repetition is intended for long-term learning as the results can appear after sev- eral weeks or even months of work. On the other hand, learning of such a great amount of material in a traditional way would be considerably more demanding and would take even more time and energy. However, spaced repetition is not suitable for learning complex material that can not be effectively broken down to smaller pieces. For example, the student could memorize the steps of a complex mathematical proof, but the “big picture” would still evade him and he will soon forget what he learned in the flood of other things. 2.1 Spacing effect Spaced repetition exploits the psychological spacing effect. What is the spacing effect and how the human memory works is described in the following citation: According to Wozniak, when we learn something for the first time we experience a slight increase in the stability and retrievability in synapses involved in cod- ing the particular stimulus-response association. In time, retrievability declines rapidly; the phenomenon equivalent to forgetting. At the same time, the stabil- ity of memory remains at the approximately same level. However, if we repeat the association before retrievability drops to zero, retrievability regains its initial value, while stability increases to a new level, substantially higher than at pri- mary learning. Before the next repetition takes place, due to increased stability, 4 2. WHAT IS SPACED REPETITION retrievability decreases at a slower pace, and the inter-repetition interval might be much longer before forgetting takes place. Two other important properties of memory should also be noted: (1) repetitions have no power to increase the stability at times when retrievability is high (spacing effect), (2) upon forgetting, stability declines rapidly. [3] In other words, too much repetitions in too short time intervals have no positive effect on better memorization. On the other hand, if the repetitions are spread too much, retrievability drops too low and the information is eventually forgotten. 2.2 Learning process There were implemented several systems utilizing the spaced repetition, but the general outline of the learning process is the same in all of them. The material that the student wants to learn is first divided into small pieces usually called items, flashcards or just cards. Each card contains a question and an answer. In one session the student is usually given cards that are scheduled for review and sev- eral new cards. The learning of one card usually looks like this: 1. The student is shown a question. 2. He has to recollect the correct answer. 3. Next, he has to evaluate whether he did or didn’t know the answer. 4. Finally, he provides a feedback of how well he knew the answer. The system then decides when the user will get the card next time. If the student knew the answer well, the card will be reviewed later than in case he didn’t know the answer. The length of intervals can span from a few days to months or even years. The computation of the review interval is the most crucial part of the algorithm. The review interval is usually calculated from the feedback the student provides and from the previously computed interval. It can involve other things too, such as the number of trials user needed to correctly answer the question or a difficulty rating of the card. Ideally, the card should be scheduled for review when the probability of recollecting the information is 90% (let’s call it retention index). This is more difficult to achieve than it sounds — the moment when the student is about to forget what he learned depends on many factors, while many of them can not be influenced or predicted. The factors include fatigue, stress, amount and type of material already learned etc. Choosing the retention index too high or too low (over 90% or below 50%) is counter- productive. If it is chosen too high, review intervals will be too short and the learning would be frustrating because of slow progress. Choosing too low retention index is useless as well because the amount of remembered information would be too
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